9 citations · 12 across the 6 of their papers we have counts for
6 papers
EXIMO: VLM Guided Exploration of VLA Policies
Bhavya Sukhija, Oliver Groth, Mohit Shridhar +5
How to efficiently finetune robot policies to learn new tasks on the fly? State of the art robotic manipulation policies are based on behaviour cloning of large vision-language-act…
Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer
Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169
General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…
Improving cosmological reach of a gravitational wave observatory using Deep Loop Shaping
Jonas Buchli, Brendan Tracey, Tomislav Andric +28
Improved low-frequency sensitivity of gravitational wave observatories would unlock study of intermediate-mass black hole mergers, binary black hole eccentricity, and provide early…
Exploiting Policy Idling for Dexterous Manipulation
Annie S. Chen, Philemon Brakel, Antonia Bronars +7
Learning-based methods for dexterous manipulation have made notable progress in recent years. However, learned policies often still lack reliability and exhibit limited robustness…
Offline Actor-Critic Reinforcement Learning Scales to Large Models
Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang +9
We show that offline actor-critic reinforcement learning can scale to large models - such as transformers - and follows similar scaling laws as supervised learning. We find that of…
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots
Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle +12
Reinforcement learning solely from an agent's self-generated data is often believed to be infeasible for learning on real robots, due to the amount of data needed. However, if done…